Method for testing a wireless link of a Wi-Fi node, and circuit performing the method

ABSTRACT

A method and a system for monitoring a wireless link of a wireless node of a CPE device during operation of the CPE device are provided, For example, the method comprises taking samples of one or several of the following parameters in a defined time interval: Received Signal Strength (RSSI), modulation rate (Physical Layer Rate) and/or the number of spatial streams used for the wireless link, and calculating an average for the one or several of the parameters by including a filtering of the one or several of the parameters.

This application claims the benefit, under 35 U.S.C. § 365 ofInternational Application PCT/EP2014/070615, filed Sep. 26, 2014, whichwas published in accordance with PCT Article 21(2) on Apr. 2, 2015 inEnglish and which claims the benefit of European Patent Application No.13306337.0, filed Sep. 27, 2013 and European Patent Application No.13306623.3, filed Nov. 27, 2013.

TECHNICAL FIELD

The invention relates to the field of wireless nodes and respectivedevices communicating with each other via a wireless communication.

BACKGROUND OF THE INVENTION

Access gateways are widely used to connect devices a the home to theInternet or any other wide area network (WAN). Access gateways use inparticular digital subscriber line (DSL) technology that enables a highdata rate transmission over copper lines or optical lines. Residentialgateways, but also other devices such as routers, switches, telephonesand set-top boxes, are understood in this context as customer premisesequipment (CPE) devices.

Access gateways including wireless technology have a key role in today'shome and professional environments. A mechanism for connecting wirelessdevices to a local area network (LAN) is called Wi-Fi, which is a brandname of the Wi-Fi Alliance for devices using the IEEE 802.11 family ofstandards for wireless data transmission. The IEEE 802.11 standardsdefine two types of wireless nodes, a general wireless device that canconnect to other devices called a station (denoted as STA) and a specialtype of a STA that is in control of the network, namely an access point(denoted AP). A Wi-Fi network, often called a WLAN (wireless local areanetwork), consists of an AP with one or several STA connected to the AP.

Due to its flexible and “invisible” nature, a lot of LAN applicationsare utilizing Wi-Fi rather than the classical wired Ethernet approach.This widespread usage of wireless LAN has exposed however a seriousdownside of using a shared medium technology: interference.Interference, both Wi-Fi and non-Wi-Fi related, leads to a degraded userexperience due to the nature of IEEE 802.11. In its most common form,IEEE 802.11 networks apply a medium access method in which collisionsare avoided by sensing that the medium is used (denoted as CSMA-CA). Themedium access method is also commonly known as “listen before talk”,describing the essence of the method. Interference from any nature canhence block the medium and force all nodes to remain silent.

A further technique that may be used to avoid interference is referredto as “Clear Channel Assessment” (CCA). Clear channel assessmentdetermines whether a wireless communication channel is “occupied”, e.g.,“busy” with another wireless communication and/or has an amount ofinterference that makes the wireless communication channel unsuitablefor communication. In this way, it is determined whether the wirelesscommunication channel is available or not available for communication,e.g. occupied or not occupied.

Another impact of interference can be packet loss at the receiver side,leading to a reduction of the physical data rate. In this case, theinterference is not detected by the CCA of the transmitter, but isdecreasing the SINR (Signal to Noise and Interference Ratio) of theWi-Fi packets as seen by the receiver.

Therefore, in certain circumstances, the Wi-Fi connection can sufferfrom poor performance and even connection loss. Some of thesecircumstances are obvious and easy to explain to an end user. Forexample, if the distance between the station and the access point is toolarge, then signal levels are low and performance will degrade. Othercircumstances are “invisible” and not understood by the end user, e.g. ahidden node. A hidden node is invisible to some of the nodes of anetwork, leading to a practical failure of the CSMA-CA method, which cancause packet collision/corruption over air. In many cases, the end useris not able to diagnose the problem source and correct the issue.

In-home Wi-Fi network connectivity is correspondingly one of the mainInternet service provider support costs and causes for help-desk calls.Today's focus for operators is mainly on Wi-Fi network installation,associating a station with an access point. Internet service providersare therefore searching for ways to get a better understanding of theend user's wireless environment including link quality and performance.

Related to Wi-Fi performance, operators can use a remote managementprotocol such as Broadband Forum (noted BBF) TR-069 protocol, whichprovides access to Wi-Fi parameters as defined in the Internet GatewayDevice data model BBF TR-181. But the information available via TR-069is very limited and focused on data traffic. In some cases, an end useris faced with an issue preventing Wi-Fi connection at all,correspondingly rendering TR-069 monitoring useless. Hence, when an enduser calls a help-desk, it can be a lengthy and expensive process todescribe the home topology and diagnose the issue at hand.

The ideal way to analyze Wi-Fi issues, e.g. connection setup,interference, throughput, . . . , is by looking into the master node ofthe wireless LAN, namely the AP. The AP, as defined in IEEE 802.11,controls the network, hence all data and network control must be visibleby the AP. The AP today can deliver statistics regarding packettransmission and signal levels, but only if a link between the AP and aSTA can be established. The real issue why a link is dropped or whythroughput is low, remains hidden to the internals of the AP. Fullpacket inspection is not possible, hence leaving technology or protocolanalyzers in the dark when it comes down to pinpointing the real issuesin a wireless LAN. Today, at best an AP can deliver statistics but noview on what is actually happening in the wireless network.

Wi-Fi performance can be degraded because of the following categories.For each category, a different action has to be taken to improve things:

-   -   Power Save settings of the Station        -   Change power save setting of the station    -   Sharing the medium (properly) with other Wi-Fi devices        -   Use another channel that is less occupied (or prioritize            Wi-Fi traffic properly using e.g. Wi-Fi Multimedia            priorities (WMM, IEEE 802.11e)    -   Interference at Transmitter side        -   Change to channel without interference (or remove            interference source)    -   Interference at Receiver side        -   Change to channel without interference (or remove            interference source)    -   Physics: high path loss, impossibility to set up multiple        spatial streams        -   move AP or Station

The problem to solve is to have an application that can correctlyanalyze Wi-Fi performance issues and indicate the correct categorycausing the issue, so that the end user can be guided to a suitablecorrective action.

SUMMARY OF THE INVENTION

The methods described rely on the availability of correct statisticsrelated to the quality of the Wi-Fi link, such as but not limited toSignal Strength (RSSI) as well as of the Modulation rate (Physical Rate)and the number of Spatial Streams used for a given Wi-Fi link. It is nota trivial task to obtain the correct statistics, as there are power savemechanisms in place that influence the above mentioned parameters insuch a way that they cannot be used as such to understand the quality ofthe Wi-Fi link. E.g. a Wi-Fi implementation can reduce the number ofspatial streams and/or the modulation rate to reduce powerconsumption—rather than in reaction to interference which would prohibitthe use of multiple spatial streams and/or of higher modulation rates.

When doing an active test—i.e. forcing traffic through the Wi-Fi link,most implementations will abandon these power-save actions, and a normalaveraging of the above-mentioned parameters will provide—in mostcases—accurate statistics that yield a correct quality assessment of theWi-Fi link. In case of Wi-Fi quality monitoring, however, such an activetest is to be avoided. So for such passively monitoring tools, a way wasfound to collect adequate statistics that can avoid power saveartefacts.

The monitoring method takes samples of the above-mentioned parameters ona short time scale, e.g. every second. Rather than taking just theaverage of the samples taken over a certain interval, (averaging iscertainly needed to obtain reliable results), a “filtered average” isused. This means that only those samples are retained for calculatingthe average that are taken at moment when sufficient traffic is flowingover the link. This can be deduced from the TxRate and RxRate parametersthat are also sampled every second. By taking the correct threshold ofTxRate and/or RxRate, the “filtered average” can avoid the artefactscaused by power save mechanisms, and ensure that only correctly“trained” values of the relevant parameters such as PhyRate, RSSI, andnumber of spatial streams are considered.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the invention are explained in more detailbelow by way of example with reference to schematic drawings, whichshow:

FIG. 1 an access point communicating with a station via a wirelesscommunication,

FIG. 2 data rates of a wireless communication according to FIG. 1,

FIG. 3 a test application including a coordinator for an active test anda monitor for a passive test,

FIG. 4 a performance data rate as a function of RSSI in dBm,

FIG. 5 a table showing maximum available data rates for IEEE standards802.11b, 802.11g and 802.11n,

FIG. 6 data rates being obtained by applying FIG. 4 to a wirelesstransmission according to IEEE 802.11n with a 20 MHz channel bandwidthand two spatial streams, and

FIG. 7 test results being displayed on a display as consecutive blocksforming a semi-circle.

DESCRIPTION OF PREFERRED EMBODIMENTS

In the following description, example methods for monitoring oranalyzing a wireless (Wi-Fi) link of a wireless node of an access point,e.g. a customer-premises equipment device, or a station are described,as well as respective circuits performing the methods. For purposes ofexplanation, various specific details are set forth in order to providea thorough understanding of preferred embodiments. It will be evident,however, to one skilled in the art that the present invention may bepracticed without these specific details.

A customer premises equipment (CPE) device includes for example acontroller, e.g. a microprocessor, a non-volatile memory, in which anoperating system is stored, a volatile memory for the operation of theCPE device, a wireless node for a wireless operation, and a broadbandconnection, e.g. an xDSL connection. The wireless node includes acomplex software driver, a physical layer with data buffers, and anantenna. A CPE device of this kind is for example an access gateway,e.g. a residential gateway, which has a central position within awireless local area network (WLAN).

The wireless node is controlled by the software driver which executes alot of background tasks during operation of the wireless node, e.g.dynamic rate adaptation, packet aggregation, channel quality monitoring,to name some. On top of signal manipulations, the wireless driver alsoembeds the IEEE 802.11 protocol stack with the associated IEEE definedmanagement and control messaging. The wireless driver will hence injecta lot of management and control packets in the data stream, making itimpossible to analyze a link by transparently looking at the data frameexchange only.

A use case is schematically depicted in FIG. 1: An access point 1communicates with a station 2 via a wireless communication 3. The accesspoint 1 includes a circuit comprising a microprocessor 10, a volatileand a non-volatile memory 11, a wireless node 12 for the wirelesscommunication, and a test application 13. The station 2 includes asecond circuit comprising a microprocessor 20, a volatile and anon-volatile memory 21, a wireless node 22 for the wirelesscommunication, and a test application 23. The wireless node 12 includesa physical layer 14 and a link layer 15, and the Wi-Fi node 22 includesa physical layer 24 and a link layer 25.

The test application 13 comprises instructions for the microprocessor 10and the test application 23 comprises instructions for themicroprocessor 20, which are included for diagnosing the wirelesscommunication 3 and which gather an information set about the wirelesscommunication 3. The information set includes in particular achievabledata rate, physical layer data rate, multiple spacial streams, channelbandwidth, medium availability and Received Signal Strength Indicator(RSSI). Test data can be gathered in a passive mode, in which a datatransmission is monitored between the access point 1 and the station 2or vice versa, or in an active mode, in which a data transmission isforced between the access point 1 and the station 2.

FIG. 2 illustrates the possibilities which have to be considered whendiagnosing the Wi-Fi performance between the access point 1 and thestation 2. An unidirectional link 3′ from the access point 1 to thestation 2 is examined. The theoretical maximum data rate 30 for thislink is given by the capabilities of the access point 1 and the station2, called here MaxNegotiatedPhyRate or MaxPhyRate, which is for example130 MB/s in case an IEEE 802.11n standard with 20 MHz channel bandwidthand two spatial streams is selected for the transmission between theaccess point 1 and the station 2. This is thus the maximum achievablelink speed, 100%, which is only a theoretical value, because for mostsituations physical limitations come into play: the received signalstrength RSSI at the station side is reduced for example due to thedistance between the access point 1 and the station 2 and path loss dueto any walls or other obstacles and reflections. Also the number ofspatial streams has to be determined. The practically attainable datarate 31, called here PhysLimitsPhyRate, is therefore less than the datarate 30.

Further performance can be lost due to interference close to the station2, which is not seen by the access point 1, called here far endinterference FEIF: this can be any microwave source like RF Babyphone,microwave oven or a hidden Wi-Fi node, and leads to a further reduceddata rate, called here TrainedPhyRate 32. Similar interference canappear at the access point 1, called here near end interference FEIF:This will reduce the available data rate 32 to a data rate 33,MediumBusyOtherWiFi. Further performance can be lost by sharing themedium with other Wi-Fi traffic, which can be caused by WLAN traffic inthe home network, but also by Wi-Fi traffic of a neighboring network.This reduced data rate 34 is called here AvailableThroughputPSoff.Another reduction of the data rate can be caused by performance lost dueto a power save mode, for example implemented in a mobile device, e.g. asmartphone. Some percentage of its time, the station 2 may be in asleeping mode, called her %PS 35. The final data rate 36, what a usercan get as the real data rate from the access point 1 to the station 2is called ThroughputPSon 36.

In order to monitor the data traffic of the physical layer, the layer 1of the OSI (Open Systems Interconnection Model) model, the traffic thatis transmitted and received by the Wi-Fi node of the residentialgateway, the residential gateway includes a test application receivingall received and transmitted packets. The test application has access tothe following blocks:

-   -   Transmit (TX) packet queue, TX packets    -   Receive (RX) packet queue, RX packets    -   Transmit/Receive signal indicators (RSSI)

The test application is illustrated in FIG. 3 as a “Diagnozer” 40, whichis a coordinator for an active test and a monitor for a passive test,and converts received data in percentages and link speeds and presentsthe results to a user. The test application 40 is connected via a databus 41 with a statistics provider application 42 included in the accesspoint 1 and a statistics provider 43 included in the station 2. The databus 41 uses for example a publish/subscribe messaging system for anexchange of control commands and data with the statistics providers 42and 43, which is independent of the operating system of the station 2.

The test application 40 requests a test request 44 or a scan request 45,which are submitted via the data bus 41 to the statistics providers 42,43. The test request 44 can be a passive monitoring test or an activetest. Via the scan request 45, lists with recognized neighboring WLANnodes are requested from the access point 1 and/or station 2. Thestatistics providers 42, 43 receive the test state information 46 of thetest request 44 and provide, when required, scan list 47, which includesall neighboring WLAN nodes being recognized when the access point 1and/or station 2 scan the WLAN channels, and “Wi-Fi Stats”, measureddata rates 48, being obtained by the tests.

The data transmitted from the transmit member, access point 1, includein particular measured data rates: MaxPhyRate 31, PhysLimitsPhyRate 31,TrainedPhyRate 32, MediumBusy, MediumBusyOtherWi-Fi 33, %PS 35,ThroughputPSon 36, etc. The data transmitted by the statistics provider43, the receive member, include in particular RSSI and the scan list.

The test request 44 is published via the data bus 41 by the testapplication 40 and includes a test identification number(TestRequest.id), MAC addresses of receive member and transmit member,(sourceMAC, destinationMAC), test type: ping or layer 2 test,configuration, etc. The test can be a normal test, in which the receivemember is a statistics provider and publishes for example stationstatistics to the test application 40. The test can be also a blindtest, in which the receive member is an associated station not providingany statistics, and the transmit member executes a test autonomously. Inthis case, the test application 40 can use information only from theaccess point 1, the transmit member. The scan request 45 is an event andpublished by the test application 40. The scan list 47 is a state and ispublished by everyone having subscribed to the scan request 45.

For the statistics being provided by an active test, the testmeasurements are synchronized between the access point 1 and the station2. For a passive monitoring, synchronization is not required.

The statistics providers 42, 43 publish locally aggregated statisticsvia the data bus 41, for example every 30 sec in case of passivemonitoring, except when interrupted by an active test. In case ofpassive monitoring, the station 2 samples RSSI and receive data ratesevery second and calculates a filtered RSSI average over the testsduration, for example 30 sec. The filtering includes for example athreshold of 1 kbps, and RSSI samples are dropped if the receive datarate is below the threshold. The RSSI samples are aggregated, when thereceive data rate is above that threshold.

For the passive monitoring, it is further important to separate issuesat the receiver side from CCA (Clear Channel Assessment) related issues.There the fact can be used that the rate adaptation algorithm in anyWLAN node aims at reducing packet loss by stepping down to lowermodulation rates and less spatial streams. If we define “TrainedPhyRate”32 as the modulation rate that is used when the link is trained, we canapproximatively assume that problems on receive side/packet loss isminimal at this physical layer rate.

Further performance loss can be caused by the CCA mechanism blocking thetransmitter to send packets. This can be assessed by using the CCAstatistics: medium busy/medium busy other Wi-Fi 33. Actual availableperformance can be assessed through CCA statistics and knowledge ofTrainedPhyRate 32, or through an active test. This is known to thoseskilled in the art.

Medium sharing: WLAN is using a shared medium concept based on a CSMA-CA(Carrier Sense Multiple Access/Collision Avoidance) medium accessmethod. Performance will drop if more devices are sharing the medium.More difficult is to distinguish what is causing the problems onreceiver side, i.e. interference>please change channel; orphysics>please move AP or STA.

Interference: The connection speed drops due to the presence ofinterference. Instead of SNR (signal to noise ratio), SiNR (signal tointerference noise ratio) applies which impacts either the physicallayer rate or the medium availability. Physics: The connection speeddrops due to SNR degradation and a reduced ability to use multiplespatial streams (MIMO: multiple-input and multiple-output). It is notedthat MIMO systems leverage on the ability to use a multitude of spatialstreams in order to achieve high link speeds.

The PhysLimitsPhyRate 31, FIG. 2, can be understood as the boundarybetween performance lost due to physical effects (“physics”) andperformance lost due to interference at the receiver side.PhysLimitsPhyRate 31 is partly defined by extrapolating what physicallayer rate would be used in case of the measured signal strength(RSSI)—in the absence of interference. This extrapolation may be basedfor example on reference measurements in a clean environment—this can bein a conducted set up or in a radiated set up. This covers performancelost due to high path loss, leading to a low signal strength.

FIG. 4 shows a diagram depicting the performance in percent, related tothe PhysLimitsPhyRate 31, as a function of RSSI in dBm. As can be seen,the data rate is essentially unaffected above an RSSI of 70 dBm, butdrops rapidly below 70 dBm and reaches zero below 90 dBm. The measuredperformance, measured layer 2 throughput in percent×correction factor1.16, is conform with the theoretical performance: PhysLimitsPhyRate 31in percent based on RSSI and number of observed spatial streams, withthe exception of a region below −85 dBm, where there is some deviation.

The maximum available physical layer rate for the transmission betweenthe access point 1 and the station 2, MaxPhyRate 30, as negotiated, canbe obtained for example from the FIG. 5 showing a table, which includesthe maximum available data rates for the IEEE standards 802.11b, 802.11gand 802.11n as a function of the number of spatial streams (MIMOConfiguration), channel bandwidth (20 or 40 MHz), and SGI (Short GuardInterval) enabled or not enabled.

The performance obtained with regard to FIG. 4 has been transformed forthe example: IEEE 802.11n with 20 MHz channel bandwidth and two spatialstreams and depicted in FIG. 6. The link layer data rate IN in Mb/s isdrawn as a function of the RSSI in dBm. For the link layer (OSI Layer 2)rate, a factor of 1.16 has to be taken into account with regard to themaximum obtainable physical layer rate of 130 Mb/s. The curve relates toa packet loss of <1%.

Alternatively, an average of the parameters: Received Signal Strength(RSSI), Modulation rate (PhyRate) and/or the number of Spatial Streamsis used, by measuring the parameters under traffic by including afiltering of the parameters, as described below, to calculate thePhysLimitsPhyRate 31.

The second factor defining PhysLimitsPhyRate 31 is related to thepossibility to set up multiple spatial streams or not. Depending on theenvironment, presence or absence of multiple reflections/spatial paths,(de-) correlation of the signal seen by the different receivers. To takethis into account, the measured average number of spatial streams isused, as used by the link under traffic.

The following use case variations are possible: Single AP and multipleSTAs running the monitoring method:

-   -   The test application runs on multiple devices, e.g. Android        devices and on the AP, diagnosing any AP-STA link whereby the        diagnosis is performed on any Android device running the test        application. As such one can run a test from an Android device        running the application. Also. as such one can run a test from        anywhere in the home—provided the application has network        connectivity—decoupled from the actual devices under test.    -   The test application runs on a single e.g. Android device and on        the AP and diagnoses any AP-STA link. The fact that a layer 2        test is used and that the AP is gathering 90% of the statistics        allows analysis of any WLAN device even if it is not running the        test application. The application will know that it is        diagnosing a device not running the test application and will        compensate for it.

The method can be used therefore as a passive monitoring applicationmonitoring the Wi-Fi performance and informing a user when any of thedescribed problems occur on its Wi-Fi link.

The method, also called here Wi-Fi™ Doctor, consists advantageously oftwo parts: an application running on client devices (Android, iOS, PC,etc . . . ) and an application running on the gateway (AP). When usingboth, optimum measurement results are obtained at both ends of thewireless link by reading critical values from the wireless drivers. Inparticular the following data are considered by the method:

-   -   Physics 1: High Path Loss        -   Distance/walls between Gateway and Station        -   Bathroom/kitchen/metal cupboards (or other metal/water)            obstructing radio path        -   Invisible construction “details” like metal screed            reinforcement mesh, “chicken wire” walls in Victorian            houses, reflective window coating, . . .    -   Physics 2: 11n-only: MIMO multiple spatial streams not OK        -   Too difficult to explain to end user.    -   NON-WLAN interference:—at Transmit-side or at Receiver-side        -   Babyphones, analogue TV senders, BlueTooth devices,            Microwave Ovens, . . .        -   But also: WLAN not recognised as WLAN: (spatially) hidden            nodes, WLAN nodes in adjacent overlapping channels        -   802.11 MAC (Medium-Access-Layer) incapable of handling            efficiently>collapse    -   Congestion: WLAN traffic from neighbouring WLANs        -   Bandwidth decreased by sharing the same medium (802.11 MAC            in action)            -   Slow Stations (11b or just a STA far away from AP)                dictate the total bandwidth!    -   Rate Adaption, see FIG. 6, at the heart of Wi-Fi        -   If Signal gets weaker>SINR decreases>Packet Loss>step back            to slower physical rates (PhyRates)        -   Same happens with increasing Noise or Interference at            RX-side        -   Rate Adaptation algorithm strives for ˜zero packet loss    -   Symptom RSSI        -   Indicator for Signal Strength    -   Symptom TrainedPhyRate 32        -   =PhyRate when traffic flowing        -   Indicator for Signal/Interference&Noise Ratio        -   Requires fast (˜second) correlation between PhyRate and Rate

802.11n introduces MIMO, multiple Spatial Streams:

-   -   System tries to set up multiple spatial streams:−different data        streams on transmitting antennas    -   Orthogonal to Rate Adaptation>separate Symptom: number of        spatial streams

Performance “Loss” by failure to use multiple spatial streams:

-   -   Big impact: E.g. 2×2: 50%    -   Known to be caused by physical effects (Physics) e.g. if no        reflections    -   Shown to be caused by Interference at RX side

Clear Channel Assessment, CCA at the heart of Wi-Fi's CSMA-CA, alsoknown as “Listen before Talk”

-   -   Wi-Fi Transceiver is continuously assessing whether the channel        is free.    -   Symptom: MediumBusy (in percent of time)

Different CCA thresholds

-   -   For Wi-Fi frames: very low threshold Efficient “Wait2”: frame        duration known>Symptom: MediumBusyOtherWiFi 33    -   For Interference: higher threshold Less efficient: duration not        known

The active test includes in particular the following steps:

-   -   Step 1: Launches Ping Test from AP to STA, e.g. an Android        device        -   Goal1: wake up TX and RX members before TX test        -   Goal2: solve #spatial streams dilemma by checking RX and TX            physical rate (PhyRate) at the AP        -   Publish TestRequest 44:            -   TestRequest.id=random number, e.g. “PingTestId”            -   sourceMAC=MAC address AP            -   destinationMAC=MAC address STA RXmember            -   type=0 (ping test)            -   Duration=5 s            -   Packet Size=100 byte            -   WMM Class=1 (best effort)        -   When test done: retrieve radioStats[testId=PingTestId],            remove TestRequest    -   Step2: Launches Active layer 2 (L2) TX test from AP to Android        STA        -   Publish TestRequest 44:            -   TestRequest.id=random number, e.g. “TXtestId”            -   sourceMAC=MAC address AP            -   destinationMAC=MAC address targeted STA (Android) RX                member            -   Type=1 (TX test)            -   Duration=10 s            -   Packet Size=1500 byte            -   WMM Class=1 (best effort)        -   When test done: retrieve radioStats[testId=TXtestId], remove            TestRequest

Step3: Display categories in percent on graphical user interface (GUI),see also FIG. 7:

-   -   %Physics=(MaxPhyRate 30−PhysLimitsPhyRate 31        (RedBorderPhyRate))/MaxPhyRate 30        -   RedBorderPhyRate 31=MAX(PhysLimitsPhyRate 31, TrainedPhyRate            32)        -   MaxPhyRate 30 in data model (QDM):            AssociatedStation[MACAddress=MAC Android Rxmember AND            associated=true].maxNegotiatedPhyRate, TrainedPhyRate in            QDM:

RadioStats[testId=TXtestId AND radio=radioID ofAP].APStats[MACAddress=BSSID].AssociatedStationStats[MACAddress=MACAndroid Rxmember].trainedPhyRateTX

-   -   PhysLimitsPhyRate 31=(look-up of        ReferencePhyRate(RSSI))×TXRXcorFac Look-up table        (RSSI>ReferencePhyRate) provided in FIGS. 4, 6    -   RSSI in QDM: RadioStats[testId=TXtestId AND radio=radioID of        Android RXmember]. STAStats[MACAddress=MAC Android        Rxmember].RSSI Blind test: use RadioStats[testId=TXtestId AND        radio=radioID of AP]. APStats[MACAddress=BSSID].        AssociatedStationStats[MACAddress=MAC Android Rxmember].RSSI    -   TXRXcorFac=max(PINGspatsUL/PINGspatsDL,1)        -   %Physics (continued)            -   PINGspatsUL in QDM: RadioStats[testId=PingtestId AND                radio=radioID of AP].                APStats[MACAddress=BSSID].AssociatedStationStats.[MAC                Address=MAC Android Rxmember]. avgSpatialStreamsRX            -   PINGspatsDL in QDM: RadioStats[testId=PingtestId AND                radio=radioID of AP].                APStats[MACAddress=BSSID].AssociatedStationStats.[MAC                Address=MAC Android Rxmember]. avgSpatialStreamsTX            -   Look Up of ReferencePhyRate(RSSI) units kbps, e.g. from                reference measurements, FIGS. 4, 6                -   For 11n 2×2: MIN (MAX ((RSSI+82)*100000/37,                    0),100000) i.e. linear between (RSSI=−82 dBm, 0                    kbps) and (RSSI=−45 dBm, 100000 kbps), 0 kbps when                    RSSI<−82 dBm, 100000 kbps when RSSI>−45 dBm                -   For 11n 1×1: MIN (MAX (RSSI+82)*60000/23, 0), 60000)                    i.e. linear between (RSSI=−82 dBm, 0 kbps) and                    (RSSI=−59 dBm, 60000 kbps), 0 kbps when RSSI<−82                    dBm, 60000 kbps when RSSI>−59 dBm        -   FEIF=(PhysLimitsPhyRate 31            (RedBorderPhyRate)−TrainedPhyRate)/MaxPhyRate        -   %What you get!=MIN (TrainedPhyRate,            ThroughputPSon×CorFac)/MaxPhyRate            -   CorFac=correction factor to translate L2 DataRate to                PhyRate>>experimentally:                -   for 11 g CorFac=2                -   for 11n (with AMPDU) CorFac is 1.43            -   ThroughputPSon in QDM: RadioStats[testId=TXtestId AND                radio=radioID of                AP].APStats[MACAddress=BSSID].AssociatedStationStats[MACAdd                ress=MAC Android Rxmember].dataRateTX        -   SharingWiFi=MediumBusyWiFi×TrainedPhyRate/MaxPhyRate−%What            you get!            -   MediumBusyOtherWiFi in QDM=sum of                RadioStats[testId=TXtestId AND radio=radioID of                AP].APStats[MACAddress=BSSID].RXTimeFractionOBSS and                RadioStats[testId=TXtestId AND radio=radioID of                AP].APStats[MACAddress=BSSID].RXTimeFractionIBSS and                RadioStats[testId=TXtestId AND radio=radioID of                AP].APStats[MACAddress=BSSID].TXTimeFraction            -   take into account traffic sent by AP in parallel to                Txtest (e.g. to other stations)            -   Note: ceiling: 100%−%Physics−%FEIF−%What you get!        -   Sleeping=MediumAvailabe×TrainedPhyRate/MaxPhyRate            -   MediumAvailable in QDM: RadioStats[testId=TXtestId AND                radio=radioID of AP].mediumAvailable            -   Note: needed as some power save mechanisms (PS-poll) are                not reflected correctly in the parameter                “powerSaveTimeFraction” (as the AP is not aware of the                exact timings).            -   Note: ceiling: 100%−%Physics−%FEIF−%What you                get!−%SharingWiFi        -   %NEIF=100%            −%Physics−%FEIF−%WhatYouGet!−%Sleeping−%SharingWiFi            -   Note: ceiling: 0% (i.e. cannot be negative).    -   Proposed on GUI in case %FEIF is dominant in test result        -   Publish ScanRequest to AP and STA under test            -   Radio=Radio id of AP and STA        -   When the two ScanList are ready: retrieve all ScanListEntry            -   ScanListEntries with a channel equal to Radio[id of                TXMember].channel                -   If present on the AP's ScanList as wells as on the                    STA's ScanList>>mark as “Sharing Channel”                -   If present on the AP's ScanList and not on the STA's                    ScanList>>mark as “Hidden for STA”                -   If present on the STA's ScanList and not on the AP's                    ScanList>>mark as “Hidden for AP”            -   ScanListEntries with a channel equal to Radio[id of                TXMember].channel −3, −2, −1, +1, +2, or +3>>mark as                “Overlapping”        -   Display only the marked ScanListEntries

For calculating losses of a wireless link of a Wi-Fi node between acustomer premises equipment device and a station in a correct manner, itis in particular important to take samples of one or several of thefollowing parameters in a defined time interval, e.g. every second:Received Signal Strength (RSSI), Modulation rate (Physical Rate) and/orthe number of spatial streams used for a given Wi-Fi link, andcalculating an average for that parameters by including a filtering ofsaid parameters. The filtering is used in particular to filter outnon-data frames, e.g. control frames, which do not contribute to theWi-Fi transmission rate.

The obtained results can be displayed for a user on a display of hisstation 2 by the test application 40 for example as consecutive blocksforming a semi-circle, as shown in FIG. 7. The data rates as explainedwith regard to FIG. 2 define the length of each block. A pointer Pvisualizes the finally attainable data rate 36, which is in thisembodiment 23% of the theoretically available data rate of 130 MB/s.Each of the blocks include a question mark Q, which can be selected bythe user for example by using a mouse or a touchpad; and by selecting aquestion mark Q, the user is informed about the problem which causes thethroughput loss leading to the contribution of this block and gives anadvice for the user, how he can improve the situation. In case of thequestion mark Q of the block 50, the user is informed that the obtaineddata rate during the test was only 28 MB/s, 23% of the theoreticallymaximum rate of 130 MB/s.

Also other embodiments of the invention may be utilized by one skilledin the art without departing from the scope of the present invention.The method as described may be used in particular for all kinds ofaccess points and stations using a wireless transmission, e.g. Wi-Fi.The invention resides therefore in the claims herein after appended.

The invention claimed is:
 1. A method for analyzing performance of awireless node, the method comprising: acquiring samples of a wirelesslink, each sample comprising a transmission rate (TxRate) or a receiverate (RxRate) of the wireless link, and a plurality of parameters of thewireless link that include Received Signal Strength (RSSI), modulationrate (Physical Layer Rate), and number of spatial streams used for thewireless link, wherein the TxRate or the RxRate is indicative of datatraffic flowing over the wireless link; filtering the samples of thewireless link that meet a threshold of the TxRate or RxRate of thewireless link; averaging at least one parameter of the plurality ofparameters of the wireless link of the filtered samples; calculating amaximum possible data rate for the wireless link on the basis of theaveraged at least one parameter of the wireless link; and reporting themaximum possible data rate for the wireless link to a user.
 2. Themethod of claim 1, wherein the threshold for the filtering is adjustedsuch that non-data frames are filtered out.
 3. The method of claim 1,wherein the samples are taken by passive monitoring during which a datatransmission is monitored between an access point and a station.
 4. Themethod of claim 1, wherein the TxRate and the RxRate are physical layerrates.
 5. The method of claim 1, wherein a scan list is establishedincluding all neighboring WLAN nodes being recognized when an accesspoint or a station scans WLAN channels, to determine near-end and/orfar-end interference.
 6. The method of claim 1, wherein the TxRate orRxRate of the wireless link and the plurality of parameters of thewireless link are sampled at the same time.
 7. The method of claim 1,wherein sampling occurs in predetermined increments of time.
 8. Themethod of claim 1, wherein each sample is synchronized in time.
 9. Acircuit for analyzing the performance of a wireless link, the circuitcomprising a processor and an antenna, wherein the processor and theantenna are configured for: acquiring samples of a wireless link, eachsample comprising a transmission rate (TxRate) or a receive rate(RxRate) of the wireless link, and a plurality of parameters of thewireless link that include Received Signal Strength (RSSI), modulationrate (Physical Layer Rate), and number of spatial streams used for thewireless link, wherein the TxRate or the RxRate is indicative of datatraffic flowing over the wireless link; filtering the samples of thewireless link that meet a threshold of the TxRate or RxRate of thewireless link; averaging at least one parameter of the plurality ofparameters of the wireless link of the filtered samples; calculating amaximum possible data rate for the wireless link on the basis of theaveraged at least one parameter of the wireless link; and reporting themaximum possible data rate for the wireless link to a user.
 10. Thecircuit of claim 9, wherein the threshold for the filtering is adjustedsuch that non-data frames are filtered out.
 11. The circuit of claim 9,wherein the samples are taken by passive monitoring during which a datatransmission is monitored between an access point and a station.
 12. Thecircuit of claim 9, wherein the TxRate and the RxRate are physical layerrates.
 13. The circuit of claim 9, wherein a scan list is establishedincluding all neighboring WLAN nodes being recognized when an accesspoint or a station scans WLAN channels, to determine near-end and/orfar-end interference.
 14. The circuit of claim 9, wherein the TxRate orRxRate of the wireless link and the plurality of parameters of thewireless link are sampled at the same time.
 15. The circuit of claim 9,wherein sampling occurs in predetermined increments of time.
 16. Thecircuit of claim 9, wherein each sample is synchronized in time.
 17. Amethod for analyzing performance of a wireless node, the methodcomprising: acquiring a plurality of samples of a wireless link, whereineach sample of the plurality of samples includes statistics including adata rate measurement of the wireless link acquired from an access pointand a measurement of a plurality of parameters of the wireless linkacquired from a station, wherein the plurality of parameters of thewireless link includes a Received Signal Strength (RSSI), modulationrate (Physical Layer Rate), and a number of spatial streams used for thewireless link; filtering out each sample that does not meet a data ratemeasurement threshold from the plurality of samples of the wireless linkto generate a subset of samples; averaging each measurement of theplurality of parameters of the subset of samples to generate an averagemeasurement for each parameter; calculating a maximum possible data ratefor the wireless link based on one of the average measurements; andreporting the maximum possible data rate for the wireless link to auser.
 18. The method of claim 17, wherein the statistics of each samplefrom the access point and the station are synchronized in time.